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Development of a Computerized Version of the Universal Soil Loss Equation
and the USGS Pollutant Loading Functions
by
Kenneth Espiritu
Project submitted to the Faculty of the Virginia Polytechnic Institute and State University
in partial fulfillment of the requirements for the degree of
Master of Engineering
in
Civil Engineering
David F. Kibler, Chairman
06/18/97Blacksburg, Virginia
ii
Development of a Computerized Version of the Universal Soil Loss Equation
and the USGS Pollutant Loading Functions
by
Kenneth Espiritu
Dr. David F. Kibler, Chairman
(ABSTRACT)
A computerized program of soil loss and pollutant loading equations wasdeveloped in a Windows PC environment. The program implements the Universal SoilLoss Equation (USLE), the Modified Universal Soil Loss Equation (MUSLE), Roehl’ssediment delivery ratio equation, and a sediment delivery ratio equation based on both theUSLE and the MUSLE. Also implemented into the program were ten pollutant loadingequations based on the USGS Nationwide Regression Equations (NRE) for predictingwater quality in urban runoff. The programs developed here will become a part of theVirginia Tech/Penn State Urban Hydrology Model (VT-PSUHM).
iii
Acknowledgments
First, I would like to thank my advisor Dr. David Kibler for giving me thisopportunity to work on this project. His guidance, support, and encouragement helpedme finish this project on time. Next, I would like to thank Dr. G.V. Loganathan foroffering financial aid and advice during graduate school and to Dr. Panayiotis Diplas forproviding me a well rounded education in the classroom. I would also like to extendthanks to Dr. Theo Dillaha for being a part of my examining committee and for critiquingmy report. Finally, I would like to thank Dr. William Cox for his support and guidancethroughout my graduate career.
During my undergraduate years, I would like to thank Dr. Joseph Sherrard for hissuggestions and advice while I was a undergraduate at Mississippi State University. Inaddition, I would especially want to express my gratefulness to Dr. Victor Zitta forinspiring me to specialize in water resources. His classes were influential in making mydecision.
Thanks go to Thanasis Papanicolaou and Newland Agbenowsi for their insightand friendship throughout my graduate career. I would also like to thank all of theHydrosystems graduate students I have met during graduate school for their support andencouragement.
Finally, special thanks go to my parents for which none of this would have beenpossible without their support and love. They have always been there in my time of needand have always encouraged me in my endeavors.
iv
Table of Contents
Abstract ............................................................................................................................... iiAcknowledgments ..............................................................................................................iiiTable of Contents ............................................................................................................... ivList of Figures...................................................................................................................... vList of Tables...................................................................................................................... viChapter 1 Introduction........................................................................................................ 1
1.1 Problem Statement.................................................................................................. 11.2 Goals and Objectives .............................................................................................. 2
Chapter 2 Background and Development of the Universal Soil Loss Equation ................. 32.1 Universal Soil Loss Equation (USLE)....................................................................... 3
2.1.1 Rainfall-Runoff Erosivity Index, R ..................................................................... 32.1.2 Soil-erodibility Factor, K..................................................................................... 52.1.3 Length-slope Factor, LS....................................................................................... 72.1.4 Cropping and Management Factor, C.................................................................. 92.1.5 Conservation Practice Factor, P......................................................................... 112.1.6 Universal Soil Loss Equation Limitations......................................................... 12
2.2 Modified Universal Soil Loss Equation (MUSLE).................................................. 122.3 Sediment Delivery Ratio.......................................................................................... 132.4 Roehl’s Sediment Delivery Ratio Equation............................................................. 132.5 Pollutant Load Equations - USGS Nationwide Regression Equations Method (NRE)......................................................................................... 14
Chapter 3 Computer Program Development..................................................................... 183.1 Program Overview ................................................................................................... 18
3.1.1 Program Features............................................................................................... 183.1.2 Program Constraints and Limitations ................................................................ 18
3.2 Program Modules..................................................................................................... 183.2.1 Universal Soil Loss Equation Module............................................................... 193.2.3 Roehl’s Sediment Delivery Ratio Module......................................................... 313.2.4 Sediment Delivery Ratio Module ...................................................................... 323.2.5 Pollutant Loading Equations Module ................................................................ 35
Chapter 4 Program Verification ........................................................................................ 364.1 Universal Soil Loss Equation Verification .............................................................. 364.2 Modified Universal Soil Loss Equation Verification............................................... 374.3 Roehl’s Sediment Delivery Ratio Verification ........................................................ 394.4 Sediment Delivery Ratio Verification...................................................................... 394.5 Pollutant Loading Verification................................................................................. 41
Appendix A Regression Equations Used in the Program for the Soil-erodibility Factor ................................................................................... 43References ......................................................................................................................... 48Vita .................................................................................................................................... 50
v
List of Figures
Figure 1 - Iso-erodent Map of the Annual Rainfall Energy Factor ..................................... 4Figure 2 - Soil Erodibility Nomograph for Determining (K) Factor for U.S. Soils............ 6Figure 3 - Length-slope Factor (LS) for Different Slopes................................................... 8Figure 4 - Fifteen Rainfall Zones in the United States...................................................... 16Figure 5 - Screenshot of Startup Menu.............................................................................. 19Figure 6 - Program Flowchart for USLE Module ............................................................. 19Figure 7 - Screenshot of USLE Module Input Form......................................................... 20Figure 8 - Screenshot of USLE Module Output Form ...................................................... 21Figure 9 - Screenshot of R Sub-module ............................................................................ 22Figure 10 - Screenshot of K Sub-module, Five Parameters .............................................. 23Figure 11 - Screenshot of K Sub-module, Two Parameters.............................................. 23Figure 12 - Screenshot of LS Sub-module ........................................................................ 24Figure 13 - Screenshot of C Sub-module, Agriculture...................................................... 25Figure 14 - Screenshot of C Sub-module, Construction ................................................... 26Figure 15 - Screenshot of P Sub-module, Agriculture ...................................................... 27Figure 16 - Screenshot of P Sub-module, Construction.................................................... 27Figure 17 - Program Flowchart for MUSLE Module........................................................ 28Figure 18 - Screenshot of MUSLE Module Input Form ................................................... 29Figure 19 - Screenshot of (Q⋅qp) Sub-module ................................................................... 29Figure 20 - Screenshot of MUSLE Module Output .......................................................... 30Figure 21 - Program Flowchart for Roehl’s Equation....................................................... 31Figure 22 - Screenshot of Roehl's Sediment Delivery Ratio Module................................ 32Figure 23 - Program Flowchart for Sediment Delivery Ratio Module.............................. 32Figure 24 - Screenshot of Sediment Delivery Ratio Input Form....................................... 33Figure 25 - Screenshot of Sediment Delivery Ratio Output Form.................................... 34Figure 26 - Program Flowchart for Pollutant Loading Module......................................... 35Figure 27 - Screenshot of NRE Pollutant Loading Module .............................................. 35Figure 28 - Hydrograph for MUSLE Example.................................................................. 38Figure 29 - Storm Hyetograph for SDR Example............................................................. 40Figure 30 - Storm Hydrograph for SDR Example............................................................. 40
vi
List of Tables
Table 1 - Magnitude of Soil Erodibility Factor, K.............................................................. 7Table 2 - Slope Factor Dependent on Field Slope............................................................... 8Table 3 - Values of C for Cropland, Pasture, and Woodland.............................................. 9Table 4 - C-Values and Slope-Length Limits (LS) for Construction Sites ....................... 10Table 5 - Values of P for Agricultural Lands.................................................................... 11Table 6 - Values of P for Construction Sites..................................................................... 11Table 7 - Regression Coefficients for Indicated Explanatory Variables........................... 14Table 8 - Annual and Individual Storm Statistic Typical Values for
Fifteen Rainfall Zones in the United States....................................................... 17
1
Chapter 1 Introduction
1.1 Problem Statement
Soil erosion has become one of the most damaging water quality problems in theworld today. This is largely produced by man’s continuing impact on the naturallandscape as undeveloped watersheds change to agricultural fields and pastures, therebyincreasing soil erosion due to the land disturbing effects of cultivation. Urbanization hasalso led to more soil erosion from construction sites where there are exposed soils. Suchland-disturbing activities can be quite damaging to the aquatic ecosystem and can carrymajor pollutants to receiving water bodies (Novotony, 1993).
Water and wind are the predominate causes of soil erosion. In most areas, wateris the primary cause of erosion. Erosion by rainfall is caused when there is no vegetativecover to dissipate the kinetic energy in a raindrop. Soil particles are then dislodged whenthe raindrop impacts the soil. The dislodged soil particles then either runoff into streamsand rivers or are redeposited onto the field. Also, vegetative roots resist the shearingeffects on the soil due to rainfall runoff reducing soil erosion. Soil loss is defined as thetotal amount of soil eroded, but may be redeposited onto the field. In contrast, sedimentyield is the sum of eroded soil minus the sediment which is deposited into depressions oralong the boundaries of the field.
Erosion prediction measurements started in the U.S. after the “dust bowl” erosionin the 1930’s. In 1965, the U.S. Department of Agriculture (USDA) developed the well-known Universal Soil Loss Equation (USLE). Requirements for the USLE were that ithad to be simple to solve and used factors which were readily available for a particularsite (Wischmeier, 1976). Later, the USLE was modified and extended to allow forcalculations of sediment yield which lead to the development of the Modified UniversalSoil Loss Equation (MUSLE) (Williams, 1977). In the 1990’s the USLE was upgradedagain to the Revised Universal Soil Loss Equation (RUSLE) (Renard et al., 1991).Development of an erosion prediction model based on physically based equations haslead to the introduction of the Water Erosion Prediction Project (WEPP) (Foster, 1991).Today, although the USLE is an empirical equation, it is used because of the simplecalculations required and the factors which are readily available for a site. Because ofthis, the USLE is still widely popular today.
2
1.2 Goals and Objectives
The primary objective of the project was to implement the universal soil lossequations into a user-friendly program. Visual Basic 4.0 was chosen as the programminglanguage because the programs from this project will become a part of VirginiaTech/Penn State Urban Hydrology Model (VT-PSUHM) which was also written in VisualBasic. In addition, data files from VT-PSUHM were integrated into the project to allowuse of hyetographs and hydrographs in the sediment yield and sediment deliveryequations. Later in the project development, the USGS pollutant loading equations wereadded to the project.
3
Chapter 2 Background and Development of the Universal Soil LossEquation
2.1 Universal Soil Loss Equation (USLE)
The universal soil loss equation was developed by the Agricultural ResearchService of the USDA and Purdue University (Novotony, 1993). It is used to estimatelong-term annual soil loss caused by water erosion. The USLE predicts soil loss based onrainfall patterns, soil type, cropping management, length and slope of the area in question,and conservation practices. The USLE is used primarily to calculate sheet and rill erosionit does not predict soil loss from gully, channel, or wind erosion. Nor does the USLEprovide direct sediment yield estimates (Novotony, 1993). Since, the USLE was based onplot lengths of 22 meters, extrapolation to larger lengths was not recommended by theauthors. The original equation is:
A = R⋅K⋅L⋅S⋅C⋅P (1)
where:A = Average soil loss in tonnes/ha for a given storm or annual periodR = Rainfall and runoff erosivity index factorK = Soil-erodibility factor, tonnes/ha (per unit of the erosion index)L = Slope length factor, dimensionlessS = Slope factor, dimensionlessC = Cropping management (vegetative cover) factor, dimensionlessP = Conservation (erosion-control) practice factor, dimensionless
2.1.1 Rainfall-Runoff Erosivity Index, R
The rainfall-runoff erosivity index describes the erosion due to both rainfall andsurface runoff. Average annual R factors can be obtained from a iso-erodent map givenby Figure 1.
4
Fig
ure
1 -
Iso-
erod
ent
Map
of
the
Ann
ual R
ainf
all E
nerg
y F
acto
r in
(to
ns/a
cre)
(St
ewar
t et
al.,
197
5).
5
Rainfall erosivity index, R, is calculated for a single storm from the sum of allE⋅D products in each rainfall period in a given storm.
( )R
E D
Ir
i ii
n
= =∑
130100
(2)
where:Rr = rainfall energy factor for a single storm, tonnes/haEi = kinetic energy of rainfall during the I-th portion of a storm, tonnes-m/ha-cm
Ei = 210 + 89 log 10 (Ii) for Ii < 7.72 cm/hrEi = 289 for Ii > 7.72 cm/hr
Ii = rainfall intensity during the I-th period of the storm, cm/hrDi = rainfall during the time interval I, cmI30 = maximum 30-minute rainfall intensity for the storm, cm/hri = rainfall hyetograph time intervaln = number of rainfall hyetograph time intervals
2.1.2 Soil-erodibility Factor, K
The soil erodibility factor, K, represents the inherent erodibility of the soil and theunits are tonnes/per unit of the rainfall erosivity index. Wischmeier determined that thereare five soil parameters that affect the soil erodibility factor for soils. These were: percentsilt plus very fine sand, percent sand greater than 0.10 mm and less than 2.0 mm, percentorganic matter, soil structure, and soil permeability. A soil erodibility nomograph (Figure2) was created from which K can be obtained. Also, Stewart provided a table (Table 1)which listed various magnitudes of soil erodibility based on soil type and organic mattercontent.
Procedure for Figure 2:
With appropriate data, enter scale at left and proceed to points representing thesoil’s percent sand (0.10-2.0 mm), percent organic matter, structure, and permeability, inthat sequence. Interpolate between plotted curves. The dotted line illustrates procedurefor a soil having:silt+very fine sand 65%sand 5%organic matter 2.8%structure 2permeability 4Solution: K=0.31.
6
Fig
ure
2 -
Soil
Ero
dibi
lity
Nom
ogra
ph f
or D
eter
min
ing
(K)
Fac
tor
for
U.S
. Soi
ls (
Wis
chm
eier
et
al.,
1971
).
7
Table 1 - Magnitude of Soil Erodibility Factor, K (Stewart et al., 1975).
K for Organic Matter Content (%)
Technical Class 0.5 4 2Sand 0.05 0.03 0.02Fine sand 0.16 0.14 0.10Very fine sand 0.42 0.36 0.28Loamy sand 0.12 0.10 0.16Loamy fine sand 0.24 0.20 0.16Loamy very fine sand 0.44 0.38 0.30Sandy loam 0.27 0.24 0.19Fine sandy loam 0.35 0.30 0.24Very fine sandy loam 0.47 0.41 0.35Loam 0.38 0.34 0.29Silt loam 0.48 0.42 0.33Silt 0.60 0.52 0.42Sandy clay loam 0.27 0.25 0.21Clay loam 0.28 0.25 0.21Silty clay loam 0.37 0.32 0.26Sandy clay 0.14 0.13 0.12Silty clay 0.25 0.23 0.19Clay 0.13-0.20
2.1.3 Length-slope Factor, LS
The length-slope factor is adjusted for field lengths which deviates from the standard to22.1 m (72.6 ft) with Equation 3. LS is affected by the length of the field and the slope of thefield. The length-slope factor is given by:
( )LSL M
=
+ +
22 10 065 0 0454 0 0065 2
.. . . S S (3)
where:L = field slope length, metersS = field slope, %M = slope factor based on field slope percent, Table 2
8
Table 2 - Slope Factor Dependent on Field Slope
Figure 3 - Length-slope Factor (LS) for Different Slopes (Stewart et al., 1975).
Slope % M<1 0.2
1 to 3 0.33 to 5 0.4
>5 0.5
9
2.1.4 Cropping and Management Factor, C
The crop management factor, C, is used to describe conservation practices such as croprotation, tillage practice, residue management, crop cover and crop productivity. In general, C isused for management techniques which protect the exposed soil surface from raindrop impact.Tables 3 and 4 show typical C values for agricultural and construction land-uses respectively.
Table 3 - Values of C for Cropland, Pasture, and Woodland (Stewart et al., 1975; Wischmeier and Smith, 1965; and Wischmeier, 1972).
Land Cover or Land Use CContinuous fallow tilled up and down slope 1.0Shortly after seeding prior to harvesting 0.3-0.8For crops during main part of growing season Corn 0.1-0.3 Wheat 0.05-0.15 Cotton 0.4 Soybean 0.2-0.3 Meadow 0.01-0.02For permanent pasture, idle land, unmanaged woodland Ground cover 85% - 100%
As grass 0.003As weeds 0.01
Ground cover 80%As grass 0.01As weeds 0.04
Ground cover 60%As grass 0.04As weeds 0.09
For managed woodland Tree canopy of 75% - 100% 0.001 Tree canopy of 40% - 75% 0.002-0.004 Tree canopy of 20% - 40% 0.003-0.01
10
Table 4 - C-Values and Slope-Length Limits (LS) for Construction Sites (Ports, 1975).
MulchType Application
(Mg/ha)Slope (%) C LS
No mulch or seeding All 1.0Straw or hay tied down by 2.25 <5 0.2 60anchoring and tracking 2.25 6-10 0.2 30equipment on slope 3.4 <5 0.12 90
3.4 6-10 0.12 454.5 <5 0.06 1004.5 6-10 0.06 604.5 11-15 0.07 454.5 16-20 0.11 304.5 21-25 0.14 23
Crushed stone 300 <15 0.05 60300 16-20 0.05 45300 21-33 0.05 30540 <20 0.02 90540 21-35 0.02 60
Wood chips 15 <15 0.08 2315 16-20 0.08 1527 <15 0.05 4527 16-20 0.05 2356 <15 0.02 6056 16-20 0.02 4556 21-33 0.02 30
Asphalt emulsion 12 m3/ha 0.03
Temporary seeding withgrain or fast-growing grasswith
During first 6weeks ofgrowth
After the6th week ofgrowth
No mulch 0.70 0.10 Straw 2.25 0.20 0.07 Straw 3.4 0.12 0.05 Stone 300 0.05 0.05 Stone 540 0.02 0.02 Wood chips 15 0.08 0.05 Wood chips 27 0.05 0.02 Wood chips 56 0.02 0.02Sod 0.01 0.01
11
2.1.5 Conservation Practice Factor, P
The conservation factor, P is used to represent erosion control land practices. The Pfactor is described as a practice which prevents dislodged soil particles from leaving the field.This type of protection would include terracing, contour farming, strip cropping, andsedimentation basins. Tables 5 and 6 give values of P for agriculture and construction land-uses.
Table 5 - Values of P for Agricultural Lands (Wischmeier and Smith, 1965).
Strip Cropping and TerracingSlope (percent) Crops Contouring Alternate Meadows Closegrown0-2.0 0.6 0.30 0.452.1-7.0 0.5 0.25 0.407.1-12.0 0.6 0.30 0.4512.1-18.0 0.8 0.40 0.6018.1-24.0 0.9 0.45 0.70>24 -1.0-
Table 6 - Values of P for Construction Sites (Ports, 1973).
Erosion Control Practice PSurface Condition with No Cover Compact, smooth, scraped with bulldozer or scraper up and down hill 1.30 Same as above, except raked with bulldozer and root-raked up and down hill 1.20 Compact, smooth, scraped with bulldozer or scraper across slope 1.20 Same as above, except raked with bulldozer and root raked across slope 0.90 Loose as a disked plow layer 1.00 Rough irregular surface, equipment tracks in all directions 0.90 Loose with rough surface >0.3 meter depth 0.80 Loose with smooth surface <0.3 meter depth 0.90
Structures Small sediment basins 0.09 ha basin/ha 0.50 0.13 ha basin/ha 0.30 Downstream sediment basin With chemical flocculants 0.10 Without chemical flocculants 0.20 Erosion control structures Normal rate usage 0.50 High rate usage 0.40Strip building 0.75
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2.1.6 Universal Soil Loss Equation Limitations
Wischmeier gave several warnings on the applicability and limitations of the USLE(Wischmeier, 1976). Because the USLE is an empirical equation, there are experimental andprediction errors inherent in it. In addition, the factors involved in the USLE do not representreal physical processes. Since the USLE was developed from cropland data, extensions to rangeland, forest land and construction sites should be done with caution. Also, Wischmeier warnedagainst using just one length slope factor for a complex watershed. He suggested that thewatershed should be divided into appropriate subareas for a proper analysis.
Primarily, the USLE was designed to be used by soil conservation planners andtechnicians. But, it has been extended and updated by both the Modified Universal Soil LossEquation (MUSLE) and the Revised Universal Soil Loss Equation (RUSLE) (Renard, 1991).These modifications are described below.
2.2 Modified Universal Soil Loss Equation (MUSLE)
This equation is a modification of the USLE by replacing the rainfall-runoff erosivityfactor R, with a runoff factor (Q × qp)
.56. This allows the use of a hydrological model forsimulating runoff. Thus, the MUSLE improves sediment yield estimates and eliminates the needfor delivery ratios required by the USLE. The USLE requires delivery ratios because the rainfall-runoff erosivity factor represents soil detachment only and not soil transport. The runoff factorof the MUSLE, in contrast, represents the energy for both soil detachment and sedimenttransport. The basic MUSLE equation is:
Y = C1 (Q qp)0.56 K L S C P (4)
where:Y = total sediment yield from an individual storm, tons or tonnesC1 = conversion factor of 95 or 11.8 for English or S.I. units respectivelyQ = storm runoff volume, ac-ft or m3
qp = peak runoff rate, cfs or m3/sK = soil-erodibility factor, tons/acre (per unit of the erosion index)L = slope length factor, dimensionlessS = slope factor, dimensionlessC = cropping management (vegetative cover) factor, dimensionlessP = conservation (erosion-control) practice factor, dimensionless
In tests with data from Texas, Oklahoma, Mississippi, Iowa, Nebraska, and Idaho. TheMUSLE usually explained 80 percent or more of the variation in individual storm sediment yieldfor each watershed. The sites used in developing the MUSLE ranged from areas of 0.01 to 234km2 and slopes ranged from less than 1 to about 30 percent (Williams, 1977).
13
2.3 Sediment Delivery Ratio
The sediment delivery ratio is the percentage of eroded soil which enters a water body atthe bottom of the area under analysis. Estimates from the delivery ratio can be used in planningboth control and water utilization structures such as dams, diversion channels, and debris basins(Vanoni, 1975). The delivery ratio can be estimated by substituting the USLE and the MUSLEinto the delivery ratio equation.
DRY
AW
Qq KLSCP
RKLSCPW
RWp p= = =
95 950 56 0 56( ) ( ). .
(5)
where:DR = delivery ratioQ = storm runoff volume, ac-ftqp = peak runoff rate, cfsR = rainfall-runoff erosivity index factor, tons/acreW = watershed area, acres
2.4 Roehl’s Sediment Delivery Ratio Equation
Based on 15 reservoirs in the Piedmont of Georgia and North and South Carolina, Roehlmeasured the sediment delivery in these regions (Roehl, 1962). The resulting statistical equationis based on geomorphological parameters of the watershed which include watershed area,watershed relief and length, and the stream bifurcation ratio. Roehl estimated erosion with theUSLE and developed the following sediment delivery ratio equation:
log . . log . log . log10 10 10 104 5 0 23 10 051 2 79DR WL
RBR= − −
− (6)
where:DR = sediment delivery ratio, %W = watershed drainage area, km2
L/R = watershed length to relief ratio (the watershed length measured from parallel to the main drainageway divided by elevation difference from drainage divide to outlet)
BR = the weighted mean bifurcation ratio, ratio of number of streams of a given order tothenumber in the next higher order within the study area
14
2.5 Pollutant Load Equations - USGS Nationwide Regression Equations Method (NRE)
The NRE is a set of regression equations which were developed from water quality datacollected across the U.S. in the Nationwide Urban Runoff Program (Athayde, 1983) and analyzedby Tasker and Driver of the U.S. Geological Survey in 1988. These equations include indrainage area, basin imperviousness, mean annual rainfall, mean minimum January temperature,and general land use categories (Debo and Reese, 1995). The NRE can estimate mean loads forchemical oxygen demand, suspended solids, dissolved solids, total nitrogen, total ammonia plusnitrogen, total phosphorus, dissolved phosphorous, total copper, total lead, and total zinc (Taskerand Driver, 1988). The equation is
[ ]M BCFa b DA cIA dMAR eMJT fX
=+ + + + +
102
(7)
where:M = mean load associated with a runoff event, poundsDA = total contributing drainage area, square milesIA = percent of total contributing drainage area, %MAR = Mean annual rainfall, inchesMJT = Mean minimum January temperatures, degrees FahrenheitBCF = Bias Correction Factora, b, c, d, e, and f are coefficients from Table 7.
Table 7 - Regression Coefficients for Indicated Explanatory Variables (Tasker and Driver, 1988).
DependentVariable
RegressionConstant
DA IA MAR MJT X2 BiasCorrection
FactorW a b c d e f (BCF)
COD 1.1174 2.0069 0.0051 1.298SS 1.5430 1.5906 0.0264 -0.0297 1.521DS 1.8449 2.5468 -0.0232 1.251TN -0.2433 1.6383 0.0061 -0.4442 1.345AN -0.7282 1.6123 0.0064 0.0226 -0.0210 -0.4345 1.277TP -1.3884 2.0825 0.0234 -0.0213 1.314DP -1.3661 1.3955 1.469CU -1.4824 1.8281 1.403PB -1.9679 1.9037 0.0070 0.0128 -0.0141 1.365ZN -1.6302 2.0392 0.0072 1.322
15
Dependent Variables:COD = Chemical Oxygen Demand, lbsSS = Suspended Solids, lbsDS = Dissolved Solids, lbsTN = Total Nitrogen, lbsAN = Total Ammonia plus Nitrogen, lbsTP = Total Phosphorous, lbsDP = Dissolved Phosphorus, lbsCU = Total Copper, lbsPB = Total Lead, lbsZN = Total Zinc, lbs
These equations can be used to predict mean annual or storm loads in areas ranging from0.015 to 1 mi2 (Tasker and Driver, 1988). Also during winter months, there will usually be verylittle runoff due to snowfall. So, the regression equations are valid only during the April throughOctober season in places with significant snowfall.
Mean annual pollutant load can be estimated by locating the site in question on the mapof Figure 4 and identifying the rainfall zone. Next, Table 8 is used to determine the expectednumber of storms/year in the rainfall zone. The total annual pollutant loading is then calculatedas:
Mean Annual Load = (M) (Annual No. of Storms) (8)
where:Mean Annual Load = the annual pollutant loading, lbs/yr.M = the mean pollutant loading, lbs/storm
16
Fig
ure
4 -
Fif
teen
Rai
nfal
l Zon
es in
the
Uni
ted
Stat
es (
Fro
m D
risc
oll e
t al
, 198
9).
17
Table 8 - Annual and Individual Storm Statistic Typical Values for Fifteen Rainfall Zones in the United States (From Driscoll et al., 1989).
RainfallZone
AnnualStormDepth (in)
AnnualNo. ofStorms
StormSeparation(hours)
Duration(hours)
Intensity(in/hr)
Volume(inches)
Avg CV Avg CV Avg CV Avg CV Avg CV Avg CVNortheast 34.6 0.18 70 0.13 126 0.94 11.2 0.81 0.067 1.23 0.50 0.95
Northeastcoastal
41.4 0.21 63 0.12 140 0.87 11.7 0.77 0.071 1.05 0.66 1.03
Mid-Atlantic
39.5 0.18 62 0.13 143 0.97 10.1 0.84 0.092 1.20 0.64 1.01
Central 41.9 0.19 68 0.14 133 0.99 9.2 0.85 0.097 1.09 0.62 1.00
NorthCentral
29.8 0.22 55 0.16 167 1.17 9.5 0.83 0.087 1.20 0.55 1.01
Southeast 49.0 0.20 65 0.15 136 1.03 8.7 0.92 0.122 1.09 0.75 1.10
East Gulf 53.7 0.23 68 0.17 130 1.25 6.4 1.05 0.178 1.03 0.80 1.19
EastTexas
31.2 0.29 41 0.22 213 1.28 8.0 0.97 0.137 1.08 0.76 1.18
WestTexas
17.3 0.33 30 0.27 302 1.53 7.4 0.98 0.121 1.13 0.57 1.07
Southwest 7.4 0.37 20 0.30 473 1.46 7.8 0.88 0.079 1.16 0.37 0.88
Westinland
4.9 0.43 14 0.38 786 1.54 9.4 0.75 0.055 1.06 0.36 0.87
PacificSouthwest
10.2 0.42 19 0.36 476 2.09 11.6 0.78 0.054 0.76 0.54 0.98
Northwestinland
11.5 0.29 31 0.23 304 1.43 10.4 0.82 0.057 1.20 0.37 0.93
PacificCentral
18.4 0.33 32 0.25 265 2.00 13.7 0.80 0.048 0.85 0.58 1.05
PacificNorthwest
35.7 0.19 71 0.15 123 1.50 15.9 0.80 0.035 0.73 0.50 1.09
18
Chapter 3 Computer Program Development
3.1 Program Overview
A computer program has been developed for the USLE, the MUSLE, and theUSGS pollutant loading equations described in Chapter 2. The program was developedin Visual Basic 4.0 and runs on PCs using Windows 95 and Windows NT. Programalgorithm development and program conceptualization time was around 500 hours. Theapproximate time to develop the source code was over 400 hours. Debugging andprogram verification involved close to 300 hours.
3.1.1 Program Features
The program is divided into five modules. Four of these modules are based onsoil erosion equations (USLE, MUSLE) and the sediment delivery ratio (SDR, Roehl’sequation), while the fifth is a pollutant loading equation module (NRE). Also, data forthe soil loss/erosion equations and sediment delivery ratio modules can be saved andloaded in the program. Multiple areas and land types can be handled by the program andtotal soil loss and averages of the total subareas can be calculated. In addition, theprogram modules handle both U.S. and S.I. units.
Since this program will eventually become a part of VT-PSUHM, integratingcomponents of VT-PSUHM was of major importance. Integration in VT-PSUHM wasachieved by allowing hyetographs created in VT-PSUHM to be used for calculating therainfall erosivity factor, R. The user can create a hyetograph based on the rainfall in acertain location and calculate the corresponding rainfall erosivity for that particular stormevent. In addition, hydrographs created by VT-PSUHM can be loaded into the programfor calculating the expression (Q × qp) in the MUSLE in order to calculate sediment yieldfrom a particular storm
3.1.2 Program Constraints and Limitations
A smaller rainfall-runoff erosivity factor map was used because of screen sizelimitations. This smaller figure shows most of the U.S. east coast. The maximum sizefor hyetograph and hydrograph data files are limited to 100 data points and 200 datapoints respectively. The program is limited to 1000 subareas.
3.2 Program Modules
The program utilizes various sub-modules for each of the parameters in the soilloss equations. Each parameter in the soil loss equation was broken into individual sub-modules to allow for code to be reused and easily modified. Each sub-module allows formany various types of data based on the variable used. These include both qualitative andquantitative variables depending on the particular soil loss factor. Equations 1 through 8were used within the sub-modules. Each sub-module usually requires more data in orderto calculate the final value of the parameter. So internally, the program keeps track of
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these variables even if the data are saved. Upon reloading of the data, the previouslysaved parameters for each sub-module are retained. Since the MUSLE and sedimentdelivery ratio are extensions of the USLE, most of the parameter code is reused in orderto keep the program size small. The startup screen is shown in Figure 5.
Figure 5 - Screenshot of Startup Menu
3.2.1 Universal Soil Loss Equation Module
The USLE implemented into the program is based on equation 1. Data requiredinclude the rainfall-runoff erosivity factor, the soil-erodibility factor, the slope-lengthfactor, the crop management factor and the conservation practice factor. The flowchartfor the USLE is shown in Figure 6. Also required are the impervious percentage of areaand the watershed area for total soil loss. An example is given in Figures 7 and 8.
Figure 6 - Program Flowchart for USLE Module
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Figure 7 - Screenshot of USLE Module Input Form
21
Figure 8 - Screenshot of USLE Module Output Form
22
R Sub-module
There are three ways of inputting data for the rainfall-runoff erosivity factor. Thefirst approach is by selecting the location and state in a drop-down box. This method cancustomized for different locations by modifying a data file. The next method is tocompute R from a hyetograph data file generated by VT-PSUHM. The rainfall erosivityfactor is calculated from equation 2. The last method is from an iso-erodent map inwhich R values can be picked from a chart via a mouse. Programming for the iso-erodentchart involved a modified finite-difference method to provide adequate linearinterpolation between the data points. Figure 9 shows the R factor module.
Figure 9 - Screenshot of R Sub-module
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K Sub-module
For the soil erodibility factor, Wischmeier developed a nomograph which requiredfive soil parameters to determine K. The author of this report has transferred thenomograph data points into a spreadsheet and a regression equation has been created foreach curve. These regression equations were then utilized in the program. Refer toAppendix A for the regression equations.
Also, a simpler method of calculating the soil erodibility factor which requires thesoil type and the percent organic matter content was implemented in the program.Figures 10 and 11 show both the five parameter and two parameter K forms.
Figure 10 - Screenshot of K Sub-module, Five Parameters
Figure 11 - Screenshot of K Sub-module, Two Parameters
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Length Slope Sub-module
The length slope factor is based on equation 3. Data required include the fieldslope length and field slope of the subarea. The slope factor M is calculated from thegiven field slope with Table 2. See Figure 12 for a screenshot of the LS factor.
Figure 12 - Screenshot of LS Sub-module
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Cropping and Management Sub-module
This sub-module has different menus depending on the type of land-use chosen bythe user. The land-use type can either be agriculture or construction and the appropriatemenu will be shown. Figures 13 and 14 show the C factor screens of the program.
Figure 13 - Screenshot of C Sub-module, Agriculture
26
Figure 14 - Screenshot of C Sub-module, Construction
27
Conservation Practice Factor Sub-module
This sub-module also uses the land-type for determining what menu to show. Pvalues for either agriculture or construction can be chosen. Refer to Figures 15 and 16 forthe appropriate screens.
Figure 15 - Screenshot of P Sub-module, Agriculture
Figure 16 - Screenshot of P Sub-module, Construction
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3.2.2 Modified Universal Soil Loss Equation Module
Most of the sub-modules used in this MUSLE module are the same as the USLEmodule except for the substitution of the runoff volume and the runoff peak expression(Q × qp) for R. Data for (Q × qp) can be entered in one of two ways. The first approach isby entering the runoff volume and runoff directly. The second method is to load ahydrograph data file created by VT-PSUHM. The runoff volume is calculated bycomputing the area under the hydrograph curve. Next, the runoff peak is obtained fromthe peak in the hydrograph curve. The data required for the MUSLE include the rainfallvolume, peak runoff, soil-erodibility factor, slope-length factor, crop management factor,and conservation practice factor. The flowchart for the MUSLE module is given inFigure 17. Figures 18, 19 and 20 show some example screens of MUSLE.
Figure 17 - Program Flowchart for MUSLE Module
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Figure 18 - Screenshot of MUSLE Module Input Form
Figure 19 - Screenshot of (Q⋅qp) Sub-module
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Figure 20 - Screenshot of MUSLE Module Output
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3.2.3 Roehl’s Sediment Delivery Ratio Module
This module is based on equation 6. The user inputs the watershed parametersand the sediment delivery ratio is calculated. Data required include the watershed area,the watershed relief and length ratio and the bifurcation ratio of the stream. Figure 21displays the flowchart for Roehl’s equation. See Figure 22 for a screenshot of Roehl’sdelivery ratio.
Figure 21 - Program Flowchart for Roehl’s Equation
Figure 22 - Screenshot of Roehl's Sediment Delivery Ratio Module
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3.2.4 Sediment Delivery Ratio Module
Because this equation is an extension of the USLE and MUSLE, the earlierprogram sub-modules were reused. Data required include the (Q × qp) expression, therainfall-runoff erosivity factor, and the watershed area. Figure 23 displays the flowchartfor the module. Both Figures 24 and 25 show screenshots of the data entry and finaloutput of the sediment delivery ratio program.
Figure 23 - Program Flowchart for Sediment Delivery Ratio Module
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Figure 24 - Screenshot of Sediment Delivery Ratio Input Form
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Figure 25 - Screenshot of Sediment Delivery Ratio Output Form
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3.2.5 Pollutant Loading Equations Module
The data required for calculating the pollutant load varies depending on thespecific pollutant. The coefficients used in the USGS Nationwide Regression Equationare given in Table 7. The number of annual storms can be retrieved from a screen in theprogram which is based on Figure 4 and Table 8. The flowchart is given in Figure 26.Figure 27 shows an example for total ammonia plus nitrogen load calculation.
Figure 26 - Program Flowchart for Pollutant Loading Module
Figure 27 - Screenshot of NRE Pollutant Loading Module
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Chapter 4 Program Verification
4.1 Universal Soil Loss Equation Verification
An erosive 100-ha farm field in Blacksburg, Virginia is situated on silt loam soil with aslope classification B (3% to 6% slope). The farmer is growing corn. Estimate theaverage annual soil loss per hectare with contour plowing. The field has a square shapewith a drainage ditch located on the side of the field. The overland slope is toward thedrainage ditch (Problem is adapted from Novotony, 1993, p. 265).
Given Solution:
From Figure 1, for Blacksburg, Virginia, R = 125 tons/acre = 280 tonnes/ha
Soil type is silt loamAssume soil has 2% organic matter contentK = 0.42 tons/acre
Assume rectangular fieldA = 100 ha = 1000000 m2
L = =1000000 1000 m
S = 4.5%
From Table 2, for 4.5% field slope, M = 0.4
( )LS =
+ ⋅ + ⋅ =
1000
22 10 065 0 454 4 5 0 0065 4 5 1842
0 42
.. . . . . .
.
For corn growing during main part of growing season, Table 3 gives C = 0.3
From Table 5, for a slope of 4.5%, P = 0.5
A = R K LS C P = (280)(0.42)(1.842)(0.3)(0.5) = 32.49 tonnes/ha
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Program Solution:
From iso-erodent map,R = 263.98 tonnes/haK = 0.4202L = 1000 mS = 4.5%LS = 1.8421C = 0.3
slope = 4.5%P = 0.5 (contouring)
% impervious = 0%W = 1 haA = 30.65 tonnes/ha
4.2 Modified Universal Soil Loss Equation Verification
A 0.193 mi2 (50-ha) land area is to be developed into a single family residential area. Thesoil map indicates that the soil is loam with the following composition (Adapted fromNovotony, 1993, p. 266):
Clay 20%Silt 35%Fine sand 20%(Silt + very fine sand) 55%Coarse sand and gravel 25%
The organic matter content of the soil is 1.5%. The soil is fine grained and thepermeability is moderate. The lot has a square shape with a drainage ditch in the center.It has been proposed to replace the ditch with a storm sewer. The average slope of the lottoward the ditch is 2.4%.
Determine sediment yield for a storm for which the hydrograph is given in Figure28. Sediment yield should be determined from the pervious areas for two differentperiods, namely, during construction when all vegetation is stripped from the soil surface(100% pervious) and subsequent to construction when 25% of the area is impermeable(streets, roofs, driveways, etc.)
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0
100
200
300
400
500
600
0 200 400 600 800 1000
time, min
flo
w, c
fs
Figure 28 - Hydrograph for MUSLE Example
Given Solution:
L = =2319.5 ft
ft2
1159 8.
Q = 2710620 ft3 = 62.227 acre-feet (Calculated by computing area under hydrograph)qp = 504.2 cfsK = 0.34 (From Figure 2)
( )LS =
+ ⋅ + ⋅
3535
2210 065 0 0454 2 4 0 0065 2 4
0.32.
.. . . . . = 0.4856
C = 1 (bare fallow ground)P = 1 (no erosion control practices)
( )Y = ⋅ ⋅ ⋅ ⋅ ⋅ ⋅95 62 227 504 2 0 34 0 4856 1 10 56. . . .. = 5170.9 tons (for 100% pervious)
Y = (5170.9)(0.75) (25% impervious) = 3877.5 tons
Program Solution:
Q = 62.18 acre-feetqp = 504.2K = 0.3533LS = 0.4856C = 1P = 1Y = 5082.2 tons (100% pervious)
Y = (5082.2 tons)(0.75) (25% impervious) = 3877.5 tons
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4.3 Roehl’s Sediment Delivery Ratio Verification
A watershed with an area of 2.2 mi2, with a basin relief of 60.1 ft and a watershedlength of 1.99 miles has a bifurcation ratio of 4.61. What is the sediment delivery ratio?
Given Solution:
W = 2.2 mi2
R = 60.1 ftL = 1.99 mi = 10507.2 ftL/R = 10507.2/60.1 = 174.829BR = 4.61
DR = 10 4.5 - 0.23 log (10⋅2.2) - 0.51 log 174.829 - 2.79 log 4.61 = 15.696 %
Program Solution:
Input Data:W = 2.2 mi2 = 1407.99 acresR = 60.1 ftL = 10507.2 ftBR = 4.61
Output Data:DR = 15.7 %
4.4 Sediment Delivery Ratio Verification
Find the sediment delivery ratio for a 25 year storm, with a duration of 60minutes. The watershed area is 0.193 mi2 (123.5 acres) and the curve number is 70. Thetime of concentration is 12 minutes.
Hyetograph and hydrograph generation from VT-PSUHM:
The hyetograph was created using the Virginia Department of Transportation(VDOT) Intensity Duration and Frequency (IDF) method for Blacksburg, VA in VT-PSUHM. Zone 6 was used and Montgomery county was chosen. Next, a 25 year designstorm was used with a duration of 60 minutes. This produced the hyetograph given byFigure 29. The hyetograph data was then saved to a file.
The SCS curvilinear hydrograph method was used with data from the previoushyetograph. The watershed area chosen was 0.193 mi2, the runoff curve number was 70,the time of concentration was 0.20 hours, and the hydrograph K-factor was left at thedefault of 484. Figure 30 shows the hydrograph generated. The hydrograph data wasalso saved to a file.
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0
1
2
3
4
5
6
7
0 20 40 60
time, min
sto
rm in
ten
sity
, in
/hr
0
20
40
60
80
100
120
140
0 20 40 60 80
time, min
flo
w, c
fsFigure 29 - Storm Hyetograph for SDRExample
Figure 30 - Storm Hydrograph for SDRExample
Given Solution:
( )DR
RW
p=
950 56.
R = 529.27 tonnes/ha = 236.1 tons/acreQ = 218238 ft3 = 5.01 acre-feetqp = 124.65 cfsW = 0.193 mi2 = 123.5 acres
( )DR =
⋅⋅
95 5 01 124 65
236103 1235
0 56. .
. .
.
= 0.1197
= 11.979%
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Program Solution:
Input data:
Data from these two files were then put into the sediment delivery ratio program and thefollowing additional data was added:
Watershed area = 123.5 acres
Output data:
Q = 5.01 acre-feetqp = 124.65 cfsR = 236.1 tons/acreW = 0.193 mi2 = 123.5 acresSDR = 11.98%
4.5 Pollutant Loading Verification (Tasker and Driver, 1988)
Given Solution:
Find the mean annual load of total nitrogen (TN), in pounds, for a 0.5 mi2
basin which is 90 percent residential with an impervious area of 30 percent and in aregion where the mean number of storms per year is 79. First compute the mean load fora storm, M, using Equation 7. Then multiply the mean storm load by the average numberof storms in a year for the location.
M = 10(X) ⋅BCF
where:X = [ a + b (DA)0.5 + c IA + f X2 ] = [-0.2433 + 1.6383(0.5) 0.5 + 0.0061(30) - 0.4442(0) ]M = 16.9 lbs
The mean annual load is then:
mean annual load of TN = (Average No. of Storms) (M) = (79) (16.9 lbs) = 1335 lbs
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Program Solution:
Input Data:Pollutant Type = Total NitrogenDrainage Area = 0.5 mi2
Output Data:M = 16.86 lbsmean annual load of TN = 1331.94 lbs
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Appendix A Regression Equations Used in the Program for the Soil-erodibility Factor
These equations are based on Figure 2. Data points from each individual curve wereimported into Excel spreadsheet and were regressed to give the best possible fit.
Percent sand and very fine silt
y = M factor, x = % silt + % very fine sand
0% sand
60%-97.5% silt and very fine sandy = 0.1232x3 - 27.603x2 + 2137.2x - 51903R2 = 0.9984
0%-60% silt and very fine sandy = 0.0023x3 + 0.8091x2 + 3.4856xR2 = 0.9993
0%-97.5% silt and very fine sandy = -0.0038x3 + 1.1449x2 + 4.7914x - 110.91R2 = 0.9951
90% sand
0%-10.9% silt and very fine sandy = -0.1164x3 + 2.2439x2 + 89.803xR2 = 0.9997
y = 99.917xR2 = 0.9992
80% sandy = -0.0916x3 + 4.2735x2 + 49.394xR2 = 0.9976
70% sandy = -0.0451x3 + 3.3743x2 + 38.234xR2 = 0.9984
60% sandy = -0.0039x3 + 1.375x2 + 51.691xR2 = 0.9992
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50% sandy = -0.0042x3 + 1.3307x2 + 43.387xR2 = 0.9995
40% sandy = -0.002x3 + 1.1556x2 + 36.442xR2 = 0.9995
30% sandy = -0.0043x3 + 1.402x2 + 20.328xR2 = 0.9995
20% sand0%-80% silt and very fine sandy = -0.0117x3 + 2.083x2 - 3.4629xR2 = 0.9984
0%-61.5% silt and very fine sandy = -0.0022x3 + 1.2424x2 + 13.439xR2 = 0.9995
61.5%-80% silt and very fine sandy = 0.0344x4 - 9.4535x3 + 969.35x2 - 43830x + 741280R2 = 0.998
15% sand0%-84% silt and very fine sandy = -0.0125x3 + 2.1862x2 - 11.804xR2 = 0.9981
0%-64%y = -0.0011x3 + 1.1603x2 + 9.1506xR2 = 0.9996
64%-84%y = -0.009x4 + 2.8848x3 - 345.44x2 + 18321x - 358591R2 = 0.9982
10% sand0%-90%y = -0.0114x3 + 2.0698x2 - 13.833xR2 = 0.9982
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0%-62.5%y = -0.0025x3 + 1.2853x2 + 1.9186xR2 = 0.9992
62.5%-90%y = -0.0059x4 + 1.9302x3 - 235.5x2 + 12714x - 252051R2 = 0.9989
5% sand0%-96%y = -0.0068x3 + 1.5301x2 - 5.0351xR2 = 0.9954
0%-61%y = 0.0009x3 + 0.9975x2 + 1.9265xR2 = 0.9994
61%-96%y = -0.0005x4 + 0.2618x3 - 43.184x2 + 2899.6x - 65306R2 = 0.9991
Percent organic matter content
y = first K approximation, x = M factor
0% organic mattery = -5E-14x3 + 2E-09x2 + 8E-05xR2 = 0.9998
1% organic mattery = -2E-13x3 + 4E-09x2 + 7E-05xR2 = 0.9998
2% organic mattery = -2E-13x3 + 4E-09x2 + 6E-05xR2 = 0.9997
3% organic mattery = -3E-13x3 + 5E-09x2 + 4E-05xR2 = 0.9997
4% organic mattery = -2E-13x3 + 4E-09x2 + 3E-05xR2 = 0.9997
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Soil Structure
x = first K approximation, y = M2 factor
1 - very fine granular0.2-0.7 approx. K rangey = 10000x - 1000R2 = 1
0-0.2 approx. K rangey = -59524x3 + 17857x2 + 809.52xR2 = 1
2 - fine granular0.2-0.7 approx. K rangey = 9999.7x - 606.54R2 = 1
0-0.2 approx. K rangey = 238095x3 - 35714x2 + 4190.5xR2 = 1
3 - medium or coarse granular0-0.2 approx. K rangey = 423280x3 - 68783x2 + 7603.2xR2 = 1
0.2-0.7 approx. K rangey = 10000x - 300R2 = 1
4 - blocky, platy, or massive0-0.7 approx. K rangey = 10000xR2 = 1
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Permeability
x = M2 factor, y = soil-erodibility factor, K
6 - very slowy = 0.0001x + 0.04R2 = 1
5 - slowy = 0.0001x + 0.02R2 = 1
4 - slow to moderatey = 0.0001xR2 = 1
3 - moderatey = 0.0001x - 0.03R2 = 1
2 - moderate to rapidy = 0.0001x - 0.06R2 = 1
1 - rapidy = 0.0001x - 0.08R2 = 1
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References
Athayde, D.N., P.E. Shelly, E.D. Driscoll, D. Gaboury, and G.B. Boyd. 1983. Results of the Nationwide Urban Runoff Program. Vol 1. Final Report. USEPA. Washington, DC.
Debo, T.N. and A.J. Reese. 1995. Municipal Storm Water Management. CRC Press. Boca Raton, FL.
Dillaha, T. 1996. Course Notes. BSE 4324 Non-point Source Pollution Control.
Driscoll, E.D., G.E. Palhegyi, E.W. Strecker, and P.E. Shelly. 1989. Analysis of Storm Event Characteristics for Selected Rainfall Gages Throughout the United States. Woodward-Clyde Consultants, prepared for USEPA. Washington, DC.
Foster, G.R. 1991. Advances in Wind and Water Erosion Prediction. J. Soil Water Conserv. 46:27-29.
Novotony, V. 1993. Water Quality: Prevention, Identification, and Management of Diffuse Pollution. Van Nostrand Reinhold. New York, NY.
Ports, M.A. 1973. Use of Universal Soil Loss Equation as a Design Standard. Water Resources Engineering Meeting, ASAE. Washington, DC.
Ports, M.A. 1975. Urban Sediment Control Design Criteria and Procedures, paper presented at the Winter Meeting, ASAE. Chicago, IL.
Renard, K.G., G.R. Foster, G.A. Weesies, and J.P. Porter. 1991. RUSLE: Revised Universal Soil Loss Equation. J. Soil Water Conserv. 46:30-33.
Roehl, J.W. 1962. Sediment Source Areas, Delivery Ratios and Influencing Morphological Factors. Publication 59. International Association of Scientific Hydrology. Commission of Land Erosion.
Stewart, B.A., D.A. Woolhiser, W.H. Wischmeier, J.H. Caro, and M.H. Frere. 1975. Control of Pollution from Cropland. U.S. EPA Report No. 600/2-75-026 orU.S.D.A. Rep No. ARS-H-5-1. Washington, DC.
Tasker, D.T. and N.E. Driver. 1988. Nationwide Regression Models for Predicting Urban Runoff Water Quality at Unmonitored Sites. Water Res. Bulletin. Vol. 24, No. 5, October 1988.
Vanoni, V.A. 1975. Sedimentation Engineering. ASCE. New York, NY.
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Williams, J.R. and H.D. Berndt. 1977. Sediment Yield Prediction Based on Watershed Hydrology. Trans. ASAE. 20:1100-2204.
Wischmeier, W.H., Johnson, C.B., and B.V. Cross. 1971. A Soil Erodibility Nomograph for Farmland and Construction Sites. J. Soil Water Conserv. 26:189-193.
Wischmeier, W.H. 1976. Use and Misuse of the Universal Soil Loss Equation. J. Soil Water Conserv. 31(1):5-9.
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Vita
Kenneth Tolentino Espiritu
Kenneth Tolentino Espiritu, son of Amado and Lilia Espiritu, was born on February 19,1972, in Pensacola, Florida. After graduation from Salem High School, Virginia Beach,Virginia, in 1990, Kenneth went on to obtain a Bachelor’s Degree in Civil Engineeringfrom Mississippi State University in December of 1994. Kenneth then continued hiseducation at Virginia Polytechnic Institute and State University towards a Master’sDegree. He received his Master’s Degree in Civil Engineering in June, 1997.